alisteshaar geospatial consultancy Railway use case
Precision Condition Assessment for Saudi Railway with alisteshaar Geospatial consultancy industry 4.0
Discover how our innovative approach combines cutting-edge drone technology and Leica RTC-360 LiDAR scanning to transform rail infrastructure assessment in Saudi Arabia.
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Conventional Rail Inspection's Limitations
Inefficient & Costly
Manual inspections consume valuable time and resources, with comprehensive assessments taking weeks to complete and costing thousands per mile of track.
Data Limitations
Traditional methods provide insufficient data density for complex intersections, missing critical details that affect safety and performance assessments.
Safety Hazards
Personnel working near active rail lines face significant risks, with track-related accidents remaining a leading cause of railway worker injuries.
Saudi Arabia's expansive rail network, spanning over 5,000 kilometers, demands more efficient and accurate inspection methods to maintain infrastructure integrity while ensuring worker safety.
Grid Inspection
Harness the power of cutting-edge geospatial technology to unlock a new era of precision rail assessment. Our advanced approach uses high-definition 3D scans to create hyper-accurate digital models of the entire rail network.
By precisely classifying every element - from tracks and catenary systems to surrounding structures - we deliver unparalleled visibility into the condition of your railway. This detailed data fuels systematic, grid-based inspections that leave no inch of the network unchecked, ensuring comprehensive evaluation and analysis.
High-Definition Point Cloud
1
Immersive point cloud visualization
Combined aerial drone surveys with terrestrial Leica RTC360 LiDAR scanning for comprehensive coverage from multiple perspectives.
2
Precise Rail Track Insights
High-accuracy GPS/RTK systems provide centimeter-level positioning across the entire assessment area, ensuring spatial accuracy.
3
Minimal Disruption
Rapid data acquisition significantly reduces track access time while eliminating human error in measurements and observations.
Advanced Analytics: Volumetric Analysis & Feature Extraction
Volumetric Analysis
Precise calculation of material quantities (±1.5% accuracy) enables informed maintenance planning by quantifying ballast volumes and detecting erosion or accumulation around tracks.
Feature Extraction
Automated identification measures critical rail components with 95%+ detection accuracy, including track geometry, rail wear, sleeper condition, and switch points.
Slope Analysis & Contour Mapping:
Our slope analysis identifies areas prone to erosion or subsidence, visualizing gradients across the terrain to support drainage design and stability assessment.
Precise contour mapping defines elevation changes at 0.1m intervals, providing critical insights into water flow patterns and potential flooding risks along the rail corridor.
Mesh Model & Raw Point Cloud:
Our advanced mesh models provide a precise, continuous surface representation of the rail corridor, enabling detailed visualization and accurate measurements of infrastructure elements for comprehensive analysis.
The raw point cloud delivers a highly detailed dataset, capturing millions of exact spatial coordinates that form the fundamental basis for all subsequent analyses, from feature extraction to volumetric calculations.
The Impact: Enhanced Safety, Efficiency, and Precision
90%
Safety Improvement
Reduction in human exposure to active rail lines, dramatically decreasing workplace hazards for inspection personnel.
8hrs
Data Collection Time
Complete assessment of large intersections finished in hours instead of days, minimizing operational disruptions.
40%
Cost Reduction
Significant savings in inspection and data processing costs compared to conventional methodologies.
<1cm
Position Accuracy
Sub-centimeter precision in measurements, essential for critical rail engineering applications.
Scaling Precision for Saudi Arabia's Rail Future
Nationwide Scalability
Our proven methodology establishes a repeatable framework for condition assessment across Saudi Arabia's entire rail network, supporting consistent maintenance standards.
AI Integration Potential
Future development includes AI/ML algorithms for automated defect detection, enabling predictive maintenance and further reducing inspection costs.
Vision 2030 Alignment
This technology directly supports Saudi Vision 2030's infrastructure development goals by enhancing transportation network reliability and safety.
A New Era for Rail Infrastructure Management
Our proof of concept successfully validated the integration of drone and LiDAR technologies for comprehensive rail condition assessment, establishing a new benchmark for infrastructure management.
This innovative approach unlocks unprecedented precision and efficiency for critical rail assets while significantly reducing safety risks and operational disruptions.
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